Angular Error Research Articles

Adaptive Robust Servo Control for Vertical Electric Stabilization System of Tank and Experimental Validation

A tracking stability control problem for the vertical electric stabilization system of moving tank based on adaptive robust servo control is addressed. This paper mainly focuses on two types of possibly fast time-varying but bounded uncertainty within the vertical electric stabilization system: model parameter uncertainty and uncertain nonlinearity. First, the vertical electric stabilization system is constructed as an uncertain nonlinear dynamic system that can reflect the practical mechanics transfer process of the system. Second, the dynamical equation in the form of state space is established by designing the angular tracking error. Third, the comprehensive parameter of system uncertainty is designed to estimate the most conservative effects of uncertainty. Finally, an adaptive robust servo control which can effectively handle the combined effects of complex nonlinearity and uncertainty is proposed. The feasibility of the proposed control strategy under the practical physical condition is validated through the tests on the experimental platform. This paper pioneers the introduction of the internal nonlinearity and uncertainty of the vertical electric stabilization system into the settlement of the tracking stability control problem, and validates the advanced servo control strategy through experiment for the first time.

A Randomized, Double-Blind Placebo Control Study on the Effect of a Blood Flow Restriction by an Inflatable Cuff Worn around the Arm on the Wrist Joint Position Sense in Healthy Recreational Athletes.

The number of blood flow restriction (BFR) training practitioners is rapidly increasing, so understanding the safety issues associated with limb occlusion is strongly needed. The present study determined the effect of BFR by an inflatable cuff worn around the arm on the wrist joint position sense (JPS) in healthy recreational athletes. In the prospective randomized, double-blind placebo control study, sixty healthy right-handed recreational athletes aged x = 22.93 ± 1.26 years were assigned to groups of equal size and gender rates: BFR, placebo, and control. The active wrist JPS was assessed in two separate sessions using an isokinetic dynamometer. The first assessment was performed with no cuffs. In the second session, a cuff with a standardized pressure was worn on the examined limb in the BFR group. In the placebo group, the cuff was uninflated. A between-session comparison in each group of collected angular errors expressed in degrees was carried out. The angular error in the BFR group was larger during the second measurement than the first one (p = 0.011-0.336). On the contrary, in the placebo (p = 0.241-0.948) and control (p = 0.093-0.904) groups, the error value in the second session was comparable or smaller. It was determined that BFR by an inflatable cuff around the arm impairs the wrist position sense. Hence, BFR training should be performed with caution.

Three-dimensional color particle image velocimetry based on a cross-correlation and optical flow method

Rainbow particle image velocimetry (PIV) can restore the three-dimensional velocity field of particles with a single camera; however, it requires a relatively long time to complete the reconstruction. This paper proposes a hybrid algorithm that combines the fast Fourier transform (FFT) based co-correlation algorithm and the Horn–Schunck (HS) optical flow pyramid iterative algorithm to increase the reconstruction speed. The Rankine vortex simulation experiment was performed, in which the particle velocity field was reconstructed using the proposed algorithm and the rainbow PIV method. The average endpoint error and average angular error of the proposed algorithm were roughly the same as those of the rainbow PIV algorithm; nevertheless, the reconstruction time was 20% shorter. Furthermore, the effect of velocity magnitude and particle density on the reconstruction results was analyzed. In the end, the performance of the proposed algorithm was verified using real experimental single-vortex and double-vortex datasets, from which a similar particle velocity field was obtained compared with the rainbow PIV algorithm. The results show that the reconstruction speed of the proposed hybrid algorithm is approximately 25% faster than that of the rainbow PIV algorithm.

The Prediction of the Angular Transmission Error of a Harmonic Drive by Measuring Noncontact Tooth Profile and Considering Three-dimensional Tooth Engagement

The Prediction of the Angular Transmission Error of a Harmonic Drive by Measuring Noncontact Tooth Profile and Considering Three-dimensional Tooth Engagement

Reliability of the active knee joint position sense test and influence of limb dominance and sex

The output of a sensorimotor performance can be measured with the joint position sense (JPS) test. However, investigations of leg dominance, sex and quality measures on this test are limited. Therefore, these potential influencing factors as well as reliability and consistency measures were evaluated for angular reproduction performance and neuromuscular activity during the active knee JPS test in healthy participants. Twenty healthy participants (10 males; 10 females; age 29 ± 8 years; height 165 ± 39 cm; body mass 69 ± 13 kg) performed a seated knee JPS test with a target angle of 50°. Measurements were conducted in two sessions separated by two weeks and consisted of two blocks of continuous angular reproduction (three minutes each block). The difference between reproduced and target angle was identified as angular error measured by an electrogoniometer. During reproduction, the neuromuscular activity of the quadriceps muscle was assessed by surface electromyography. Neuromuscular activity was normalized to submaximal voluntary contraction (subMVC) and displayed per muscle and movement phase. Differences between leg dominance and sex were calculated using Friedman-test (α = 0.05). Reliability measures including intraclass correlation coefficient (ICC), Bland–Altman analysis (bias ± limits of agreement (LoA)) and minimal detectable change (MDC) were analysed. No significant differences between leg dominance and sex were found in angular error and neuromuscular activity. Angular error demonstrated inter-session ICC scores of 0.424 with a bias of 2.4° (± 2.4° LoA) as well as MDC of 6.8° and moderate intra-session ICC (0.723) with a bias of 1.4° (± 1.65° LoA) as well as MDC of 4.7°. Neuromuscular activity for all muscles and movement phases illustrated inter-session ICC ranging from 0.432 to 0.809 with biases between − 2.5 and 13.6% subMVC and MDC from 13.4 to 63.9% subMVC. Intra-session ICC ranged from 0.705 to 0.987 with biases of − 7.7 to 2.4% subMVC and MDC of 2.7 to 46.5% subMVC. Leg dominance and sex seem not to influence angular reproduction performance and neuromuscular activity. Poor to excellent relative reliability paired with an acceptable consistency confirm findings of previous studies. Comparisons to pathological populations should be conducted with caution.

Method of gaze extraction in bionic vision

Aiming at the low efficiency of information processing in a robot vision system, our work studies how to extract fixed points during tasks so that significant and interesting target areas in the scene can be located. First, the architecture of a gaze extraction model of bionic vision is proposed, which consists of a spatial visual saliency model and a task-driven fixed point extraction model. The task-driven fixed point extraction process is represented as a closed-loop control problem. To couple exploration with the sampling process, a Q learning algorithm based on a random strategy is adopted, which is a top-down task-driven gaze extraction in the time dimension. It is fused with the spatial-based visual saliency model to form a spatiotemporal hybrid gaze extraction model to determine the fixed point in the final image. Finally, our qualitative image visualization experiment indicates that the fixed point extraction results of the model in two consecutive frames are close to the truth value obtained by an eye tracker. The quantitative area under the curve and average angular error data confirms the effectiveness of the model in predicting and extracting fixed points.

Dynamic Modeling and Motion Control Strategy of Cable-Driven Cleaning Robot for Ship Cargo Hold

Ship cargo-hold cleaning is a low-efficiency and high-risk operation in marine industry, which is generally carried out manually, putting the workers in danger. To improve the efficiency and safety of ship cargo-hold cleaning, a C-DCR is proposed in this article. Most research on the dynamics and control of CDPRs has focused on the scenarios with fixed bases; however, the effect of moving-base excitation on the end-effector is largely ignored. In this article, the dynamic model is established based on Lagrange method considering the ship motion and external disturbance, in which the motor model is considered. On this basis, for the high-speed maneuverability of the C-DCR, a modified PD feedforward tracking controller was proposed. Furthermore, the stability of the controller was proved with the Lyapunov Stability Theory. To keep the cable in tension at all times, the tensions are optimized based on the minimum 2-norm method. The simulation results show that the error mean of position is 0.22 m and the angular error mean is 2.8° under ship motion and external disturbance, indicating that the C-DCR has stable, smooth and bounded tracking performance, which will ensure the accuracy of the cleaning operation.

Multi-row self-balancing device with regard to eccentricity and angular error

A model of a self-balancing deviceis proposed in the article;it is installed with an eccentricity relative to the axis of symmetry of the rotor, and the ball races have a certain horizontal axis of rotation, that is, the balancing masses have an additional degree of Based on differential equations of motion, the issue of the existence of stationary motions was investigated for various combinations of the installation of a balancing system, with regard to certain eccentricity and angular error, and the rotation of the ball races around the horizontal axis. The numerical solution of the differential equations of motion of the rotor with two balancing balls is obtained and the analysis of the obtained results is conducted.

EXPERIMENTAL STUDY OF CURRENT SENSORS OF 0.38 KV VOLTAGE CLASS IN THREE MODES OF OPERATION OF THE ELECTRICAL GRID

The operation of existing relay protection devices is based on the measurement of electrical network parameters (voltage, frequency, current) performed using sensors installed in the electrical network. Current sensors are subject to high requirements for output data in various modes of operation of the electrical network. As current sensors in the 0.38 kV electrical grid, the following are widely used: current transformers, transreactor sensors, resistive sensors, Hall effect current sensors. (Research purpose) The research purpose is experimentally studying current sensors of various types used in electrical networks of 0.38 kilovolts. (Materials and methods) Conducted laboratory studies on a prepared laboratory stand of various current sensors in three operating modes: steady-state mode, switching mode with initial magnetic flux, switching mode without initial magnetic flux. (Results and discussion) It has been shown that not all types of current sensors can be used as a source of reference data in the construction of high-speed current protection. It was determined that transformer-type sensors can introduce a significant error in the operation of relay protection for reasons of significant angular error, pronounced processes of magnetization and enticement in switching modes. It was found that sensors based on the types of transreactor and Hall effect have the lowest angular error and resistance to switching modes. (Conclusions) It was revealed that when choosing current sensors as a source of reference data, not only passport characteristics, but also laboratory studies should be taken into account. The necessity of taking into account the operational operating time and inductance of the current sensor, the angular error and the shape of the current curve of the secondary circuit was stated.

Novel kinematic model of articulated arm coordinate measuring machine with angular position measurement errors of rotary axes

The measurement accuracy of an articulated arm coordinate measuring machine (AACMM) is determined by its kinematic model to estimate the end effector position from angular positions of rotary axes. In conventional studies, the Denavit–Hartenberg (DH) model, containing position and orientation errors of the rotary axis average lines as error sources, has been widely employed. This study first proposes a novel kinematic model including angular position measurement errors of rotary axes. To identify the proposed model, a new Single Point Articulation Test (SPAT) setup is presented with the R-Test to measure the stylus sphere's three-dimensional displacement. The prediction accuracy of the proposed model is experimentally evaluated.

Nonlinear dynamics of rotor of an auto-balancing ball device, considering eccentricity and changes in horizontal axes of rotation

This study is devoted to the dynamics of an auto-balancing device (ABD) when the rotor rotates at critical angular speeds. In this article, a model of an auto-balancing device (ABD) is proposed. The rotor is not only eccentric about the symmetry axis but also has a horizontal axis of rotation. A mathematical model is proposed based on the Lagrange equations; it describes the nonlinear motion of a balancing system (BS) with two running lines with a different number of balls, considering eccentricity, angular error, and changes in the horizontal axis of rotation. The nonlinear dynamics of the rotor motion with two running lines and two balls at a constant rotation speed and in the accelerating mode of the rotor motion is studied by a numerical method, taking into account the change in the horizontal axis of rotation.

Dense Scene Flow Estimation with the GVF Snake Model for Obstacle Detection Using a 3D Sensor in the Path-Planning Module

Abstract The novel framework for estimating dense scene flow using depth camera data is demonstrated in the article. Using these estimated flow vectors to identify obstacles improves the path planning module of the autonomous vehicle's (AV) intelligence. The primary difficulty in the development of AVs has been thought to be path planning in cluttered environments. These vehicles must possess the intelligence to recognize their surroundings and successfully navigate around obstacles. The AV needs a thorough understanding of the surroundings to detect and avoid obstacles in a cluttered environment. Therefore, when determining the course, it is preferable to be aware of the kinematic behavior (position and the direction) of the obstacles. As a result, by comparing the depth images between different time frames, the position and direction of the obstacles are calculated using a 3D vision sensor. The current study focuses on the extraction of the flow vectors in 3D coordinates from the differential scene flow method. Generally, the evaluation of scene flow algorithms is crucial in determining their accuracy and effectiveness in different applications. The gradient of the vector field snake model, which extracts changes in pixel values in three directions, is combined with the scene flow technique to identify both static and dynamic obstacles. Our goal is to create a single-vision sensor-based real-time obstacle avoidance method based on scene flow estimation. In addition, the common evaluation metrics such as endpoint error (EPE), average angular error (AAE), and standard deviation angular error (STDAE) are used to measure the accuracy of different algorithms in terms of computational errors with the benchmark Middlebury datasets. The proposed technique is validated with different experiments using a Pixel-Mixed-Device (PMD) camera and a Kinect sensor as 3D sensors. Finally, the numerical and experimental results are displayed and reported.

A Compact In Situ Ranging LiDAR and Performance Evaluation

To capture and process environmental information, a compact lab-built LiDAR is designed and constructed. The lab-built LiDAR utilizes a programmable-scanning-pattern image-space scanner, which is able to satisfy the demands for diverse applications, and a Gauss–Newton (GN) iteration-based in situ ranging system, which is capable of retrieving target distance at high measurement repetition rate. In order to evaluate the angular resolution of the lab-built LiDAR, a trapezoid-fitting method is proposed to quantify the gradually being blurred profile of cubic target, which was validated by the lab-built LiDAR and a commercial LiDAR. Experiments were conducted for the verification of lab-built LiDAR from ranging error, angular error, and angular resolution. The results show that the lab-built LiDAR is able to obtain a target point cloud with a ranging accuracy within [−8, 8] mm, a precision of 4–16 mm, an angular error smaller than 0.26°, and an angular resolution of 6.2 mrad. The proposed LiDAR and evaluation method will benefit hazard detection and avoidance in aerospace applications.

Analysis of Coupling Efficiency in Optic Gyroscope Transceiver Module With Elliptical Core Fiber

Improving the coupling efficiency of the optical transceiver module in fiber optic gyroscopes (FOGs) benefits both the working efficiency of the module and the signal-to-noise ratio of the FOG system. In this work, a single-mode fiber (SMF) with an elliptical mode field distribution is proposed as the coupling fiber for the FOG transceiver module. The coupling efficiency of the transceiver module using fibers with different mode field distributions at the endface is analyzed. Two structure schemes of the transceiver module are compared: one focuses the beam directly onto the endface of the fiber, and the other collimates the beam and then converge it. The optimal coupling efficiency can reach above 91.5% when the horizontal and vertical mode field radii of the fiber endface are approximately 4.05 μm and 3.37 μm respectively. The influence of the axial and angular alignment errors of the pigtail on the coupling efficiency is also investigated. The maximum tolerance of the axial alignment reaches approximately ±40.10 μm and ±30.08 μm for the two structure schemes. The maximum tolerance of the angular alignment reaches approximately ±4.4° and ±5.2° in the horizontal direction, and approximately ±3.5° and ±3.6° in the vertical direction, respectively. These tolerances are favorable for practical applications.

Automated Orientation and Registration of Cone-Beam Computed Tomography Scans.

Automated clinical decision support systems rely on accurate analysis of three-dimensional (3D) medical and dental images to assist clinicians in diagnosis, treatment planning, intervention, and assessment of growth and treatment effects. However, analyzing longitudinal 3D images requires standardized orientation and registration, which can be laborious and error-prone tasks dependent on structures of reference for registration. This paper proposes two novel tools to automatically perform the orientation and registration of 3D Cone-Beam Computed Tomography (CBCT) scans with high accuracy (<3° and <2mm of angular and linear errors when compared to expert clinicians). These tools have undergone rigorous testing, and are currently being evaluated by clinicians who utilize the 3D Slicer open-source platform. Our work aims to reduce the sources of error in the 3D medical image analysis workflow by automating these operations. These methods combine conventional image processing approaches and Artificial Intelligence (AI) based models trained and tested on de-identified CBCT volumetric images. Our results showed robust performance for standardized and reproducible image orientation and registration that provide a more complete understanding of individual patient facial growth and response to orthopedic treatment in less than 5 min.

An adaptive neuro-fuzzy based on a fractional-order proportional integral derivative design for a two-legged robot with an improved swarm algorithm

In this paper, an adaptive neuro-fuzzy based on fractional-order proportional-integral-derivative (ANFFOPID) controller with an improved slime mould algorithm (ISMA) for the two-legged robot (TLR) is proposed to achieve the minimum angular displacement error of the joint motors. Achieving such error is considered a challenging and time-consuming process due to the gain values set for the FOPID controller. Thus the neural-fuzzy network is used to provide the FOPID input signals by the adaptive magnitude gains. The adaptive mechanism depends on the ISMA to train the neural network weights. The outstanding properties of the ANFFOPID controller are evaluated by comparing the proposed controller with other existing work that is modified chaotic invasive weed optimization based on neural network (MCIWO-NN) for various walking terrains that are flat surface, stair ascending, and stair descending. Finally, the results obtained show the effectiveness of the ANFFOPID controller.

Asymptotically stable optimal multi-rate rigid body attitude estimation based on lagrange-d'alembert principle

&lt;abstract&gt;&lt;p&gt;The rigid body attitude estimation problem is treated using the discrete-time Lagrange-d'Alembert principle. Three different possibilities are considered for the multi-rate relation between angular velocity measurements and direction vector measurements for attitude: 1) integer relation between sampling rates, 2) time-varying sampling rates, 3) non-integer relation between sampling rates. In all cases, it is assumed that angular velocity measurements are sampled at a higher rate compared to the inertial vectors. The attitude determination problem from two or more vector measurements in the body-fixed frame is formulated as Wahba's problem. At instants when direction vector measurements are absent, a discrete-time model for attitude kinematics is used to propagate past measurements. A discrete-time Lagrangian is constructed as the difference between a kinetic energy-like term that is quadratic in the angular velocity estimation error and an artificial potential energy-like term obtained from Wahba's cost function. An additional dissipation term is introduced and the discrete-time Lagrange-d'Alembert principle is applied to the Lagrangian with this dissipation to obtain an optimal filtering scheme. A discrete-time Lyapunov analysis is carried out to show that the optimal filtering scheme is asymptotically stable in the absence of measurement noise and the domain of convergence is almost global. For a realistic evaluation of the scheme, numerical experiments are conducted with inputs corrupted by bounded measurement noise. These numerical simulations exhibit convergence of the estimated states to a bounded neighborhood of the actual states.&lt;/p&gt;&lt;/abstract&gt;

Extending arterial stiffness assessment along the circumference using beam-steered ARFI and wave-tracking: A proof-of-principle study in phantoms and ex vivo

BackgroundTo fully quantify arterial wall and plaque stiffness, acoustic radiation force impulse (ARFI)-induced wave-tracking along the entire vessel circumference is desired. However, attenuation and guided wave behavior in thin vessel walls limits wave-tracking to short trajectories. This study investigated the potential of beam-steered ARFI and wave-tracking to extend group velocity estimation over a larger proportion of the circumference compared to conventional 0° ARFI-induced wave-tracking. MethodsSeven vessel-mimicking polyvinyl alcohol cryogel phantoms with various dimensions and compositions and an ex vivo human carotid artery were imaged in a dedicated setup. For every 20⁰ phantom rotation, transverse group wave velocity measurements were performed with an Aixplorer Ultimate system and SL18–5 transducer using 0⁰/20⁰/−20⁰-angled ultrasound pushes. Transmural angular wave velocities were derived along 60⁰-trajectories. A 360⁰-angular velocity map was composed from the top-wall 60⁰-trajectories 0°-data, averaged over all physical phantom rotations (reference). For each phantom rotation, 360⁰-angular velocity maps were composed using 0°-data (0⁰-approach) or data from all angles (beam-steered approach). Percentages of rotations with visible waves and relative angular velocity errors compared to the reference map as function of the circumferential angle were determined for both approaches. ResultsReference 360°-angular velocity maps could be derived for all samples, representing their stiffness. Beam-steering decreased the proportion of the circumference where waves were untraceable by 20% in phantoms and 10% ex vivo, mainly at 0° push locations. Relative errors were similar for both approaches (phantoms: 10–15%, ex vivo: 15–35%). ConclusionBeam-steering enables wave-tracking along a higher proportion of the wall circumference than 0⁰ ARFI-induced wave-tracking.

Hybrid InSARTrac for monitoring interglacial movement patterns

InSARTrac is a hybrid 3D monitoring method, for which controlled field measurements have indicated significant potential for geotechnical applications. Various approaches can be taken to derive 3D displacements from InSAR measurements, such as combining multiple InSAR ascending and descending satellite passes or combining multi-geometrical radar datasets from ground and satellite based radars. InSARTrac is a cost-effective solution requiring only one terrestrial InSAR device and a camera used for feature tracking. This study summarizes the results of glacial displacement measurements that were conducted to test the InSARTrac methodology. The InSARTrac 3D displacement vectors show details concerning glacial retreat dynamics related to a combination of ice flow and volume loss. By extrapolating prior results obtained from controlled field measurements, the resultant displacement vector orientations have an estimated angular error of approximately 5 degrees. With a fixed camera mount and longer monitoring times this error can be further reduced. Current studies are focused on deploying InSARTrac to investigate its potential for landslide and geostructure monitoring.

Uncertainty-aware Gaze Tracking for Assisted Living Environments.

Effective assisted living environments must be able to infer how their occupants interact in a variety of scenarios. Gaze direction provides strong indications of how a person engages with the environment and its occupants. In this paper, we investigate the problem of gaze tracking in multi-camera assisted living environments. We propose a gaze tracking method based on predictions generated by a neural network regressor that relies only on the relative positions of facial keypoints to estimate gaze. For each gaze prediction, our regressor also provides an estimate of its own uncertainty, which is used to weigh the contribution of previously estimated gazes within a tracking framework based on an angular Kalman filter. Our gaze estimation neural network uses confidence gated units to alleviate keypoint prediction uncertainties in scenarios involving partial occlusions or unfavorable views of the subjects. We evaluate our method using videos from the MoDiPro dataset, which we acquired in a real assisted living facility, and on the publicly available GazeFollow and Gaze360 datasets. Experimental results show that our gaze estimation network outperforms sophisticated state-of-the-art methods, while additionally providing uncertainty predictions that are highly correlated with the actual angular error of the corresponding estimates. Finally, an analysis of the temporal integration performance of our method demonstrates that it generates accurate and temporally stable gaze predictions.